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      name:  <unnamed>
       log:  F:\log.log
  log type:  text
 opened on:  25 Apr 2021, 12:59:29

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. *     File-Name:  DO.do                                                 *

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. *     Date:       April 2021                                            *

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. *     Author:     ***** *****                                           *

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. *     Purpose:    National Images  (APP 2021)                           *

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. *     Input File: CCES12_FSB_OUTPUT.dta                                 *

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. *     Output File: log.log                                              *

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. *     Data Output: None                                                 *

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. *     Program:  Stata 14                                              *

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. *     Machine:    (Toshiba)Laptop                                       *

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. *     ****************************************************************  *

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. *     ****************************************************************  *

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. *     ****************************************************************  *

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. *                     Install Clarify                                   *

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. *     ****************************************************************  *

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. net from https://gking.harvard.edu/clarify/
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https://gking.harvard.edu/clarify/
Clarify: Software to Interpret and Present Statistical Results
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Michael Tomz         Jason Wittenberg          Gary King
Stanford Univ.   Univ. of Wisconsin, Madison   Harvard Univ.


To install Clarify, type net install clarify
To download documentation to your working directory, type net get clarify
For a brief description of Clarify, type net describe clarify

PACKAGES you could -net describe-:
    clarify           Software to Interpret and Present Statistical Results
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

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. net install clarify
checking clarify consistency and verifying not already installed...
all files already exist and are up to date.

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. *     ****************************************************************  *

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. *                      Treatments                                       *

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. *     ****************************************************************  *

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. gen econA = 1 if FSB416a <101
(792 missing values generated)

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. replace econA = 0 if FSB416a==999
(603 real changes made)

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. replace econA = . if FSB416a==.
(0 real changes made)

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. gen econB = 1 if FSB416b <101
(792 missing values generated)

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. replace econB = 0 if FSB416b==999
(603 real changes made)

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. replace econB = . if FSB416b==.
(0 real changes made)

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. gen econC = 1 if FSB416c <101
(793 missing values generated)

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. replace econC = 0 if FSB416c==999
(603 real changes made)

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. replace econC = . if FSB416c==.
(0 real changes made)

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. gen econ_sum = econA + econB + econC
(194 missing values generated)

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. gen econ = 1 if econ_sum ==3
(797 missing values generated)

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. replace econ = 0 if econ_sum ==0
(603 real changes made)

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. replace econ = . if econ_sum ==.
(0 real changes made)

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. gen polA = 1 if FSB417a <101
(805 missing values generated)

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. replace polA = 0 if FSB417a==999
(620 real changes made)

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. replace polA = . if FSB417a==.
(0 real changes made)

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. 
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. gen polB = 1 if FSB417b <101
(802 missing values generated)

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. replace polB = 0 if FSB417b==999
(620 real changes made)

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. replace polB = . if FSB417b==.
(0 real changes made)

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. gen polC = 1 if FSB417c <101
(807 missing values generated)

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. replace polC = 0 if FSB417c==999
(620 real changes made)

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. replace polC = . if FSB417c==.
(0 real changes made)

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. gen pol_sum = polA + polB + polC
(189 missing values generated)

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. gen pol = 1 if pol_sum ==3
(809 missing values generated)

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. replace pol = 0 if pol_sum ==0
(620 real changes made)

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. replace pol = . if pol_sum ==.
(0 real changes made)

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. gen cultA = 1 if FSB418a <101
(810 missing values generated)

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. replace cultA = 0 if FSB418a==999
(624 real changes made)

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. replace cultA = . if FSB418a==.
(0 real changes made)

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. gen cultB = 1 if FSB418b <101
(809 missing values generated)

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. replace cultB = 0 if FSB418b==999
(624 real changes made)

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. replace cultB = . if FSB418b==.
(0 real changes made)

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. gen cultC = 1 if FSB418c <101
(808 missing values generated)

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. replace cultC = 0 if FSB418c==999
(624 real changes made)

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. replace cultC = . if FSB418c==.
(0 real changes made)

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. gen cult_sum = cultA + cultB + cultC
(189 missing values generated)

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. gen cult = 1 if cult_sum ==3
(813 missing values generated)

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. replace cult = 0 if cult_sum ==0
(624 real changes made)

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. replace cult = . if cult_sum ==.
(0 real changes made)

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. gen treat_sum = econ + pol + cult
(216 missing values generated)

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. gen control = 1 if treat_sum ==0
(797 missing values generated)

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. replace control = 0 if treat_sum ==1
(581 real changes made)

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. gen sample_sum = econ + pol + cult + control
(216 missing values generated)

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. gen man_check = econ + pol + cult + control
(216 missing values generated)

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. drop if man_check==.
(216 observations deleted)

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. *     ****************************************************************  *

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. *            DV                                                         *

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. *     ****************************************************************  *

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. gen supptrade = FSB419

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. recode supptrade (8=.)
(supptrade: 1 changes made)

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. drop if supptrade==.
(1 observation deleted)

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. *     ****************************************************************  *

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. *           Control Variables                                           *

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. *     ****************************************************************  *

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. gen age = 2013-birthyr

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. gen female = 1 if gender==2
(370 missing values generated)

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. replace female = 0 if gender==1
(370 real changes made)

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. gen union1 = 1 if union ==1|union ==2
(570 missing values generated)

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. recode union1 (.=0)
(union1: 570 changes made)

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. gen socio = CC302

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. recode socio (6=.)
(socio: 4 changes made)

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. gen married = 1 if marstat ==1|marstat==6
(284 missing values generated)

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. recode married (.=0)
(married: 284 changes made)

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. gen unempl = 1 if employ==4
(716 missing values generated)

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. recode unempl (.=0)
(unempl: 716 changes made)

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. gen conservative = 1 if pid3==1
(531 missing values generated)

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. replace conservative =2 if pid3==3
(237 real changes made)

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. replace conservative =3 if pid3==2
(239 real changes made)

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. gen lowinc = 1 if faminc<6
(489 missing values generated)

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. replace lowinc=0 if faminc>5
(489 real changes made)

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. gen coll_grad = 1 if educ ==5|educ==6
(477 missing values generated)

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. replace coll_grad = 0 if educ<5
(477 real changes made)

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. drop  if immstat==2|immstat==8
(10 observations deleted)

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. *     ****************************************************************  *

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. *           Descriptive Statics                                         *

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. *     ****************************************************************  *

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. sum coll_grad lowinc age female union1 socio married unempl conservative supptrade control econ pol cult if control==1|econ==1|pol==1|cult==1

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
   coll_grad |        773    .3906856      .48822          0          1
      lowinc |        773    .3751617    .4844781          0          1
         age |        773    55.64166    15.17035         19         91
      female |        773    .5278137     .499549          0          1
      union1 |        773    .2742561    .4464275          0          1
-------------+---------------------------------------------------------
       socio |        769    3.276983     1.14109          1          5
     married |        773    .6377749    .4809546          0          1
      unempl |        773    .0866753    .2815408          0          1
conservative |        721    1.979196    .8221651          1          3
   supptrade |        773    3.310479    .9087122          1          5
-------------+---------------------------------------------------------
     control |        773    .2600259    .4389324          0          1
        econ |        773    .2587322    .4382217          0          1
         pol |        773    .2432083    .4292976          0          1
        cult |        773    .2380336    .4261556          0          1

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. sum coll_grad lowinc age female union1 socio married unempl conservative supptrade if control ==1 

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
   coll_grad |        201    .3631841     .482118          0          1
      lowinc |        201    .4029851    .4917225          0          1
         age |        201     56.9204     15.0988         19         87
      female |        201    .5572139     .497956          0          1
      union1 |        201    .3283582    .4707885          0          1
-------------+---------------------------------------------------------
       socio |        200        3.27    1.176444          1          5
     married |        201    .6865672    .4650469          0          1
      unempl |        201    .0895522    .2862522          0          1
conservative |        193    1.906736    .8426188          1          3
   supptrade |        201     3.20398    .9397787          1          5

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. sum coll_grad lowinc age female union1 socio married unempl conservative supptrade if econ ==1 

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
   coll_grad |        200         .37    .4840159          0          1
      lowinc |        200        .375    .4853378          0          1
         age |        200       56.64    14.46154         19         91
      female |        200        .545    .4992205          0          1
      union1 |        200        .305    .4615628          0          1
-------------+---------------------------------------------------------
       socio |        198    3.343434    1.132462          1          5
     married |        200         .63    .4840159          0          1
      unempl |        200         .11    .3136749          0          1
conservative |        185    1.967568    .8069178          1          3
   supptrade |        200        3.37    .9095253          1          5

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. sum coll_grad lowinc age female union1 socio married unempl conservative supptrade if pol ==1 

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
   coll_grad |        188    .4308511    .4965176          0          1
      lowinc |        188    .3617021    .4817762          0          1
         age |        188    55.39894    14.81419         20         84
      female |        188    .4840426    .5010797          0          1
      union1 |        188    .2446809    .4310457          0          1
-------------+---------------------------------------------------------
       socio |        187    3.262032    1.131562          1          5
     married |        188    .6276596    .4847193          0          1
      unempl |        188    .0797872    .2716871          0          1
conservative |        171    2.070175    .8013147          1          3
   supptrade |        188     3.37766    .8719827          1          5

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. sum coll_grad lowinc age female union1 socio married unempl conservative supptrade if cult ==1 

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
   coll_grad |        184    .4021739    .4916746          0          1
      lowinc |        184    .3586957    .4809263          0          1
         age |        184    53.40761    16.18851         20         91
      female |        184    .5217391    .5008902          0          1
      union1 |        184    .2119565    .4098093          0          1
-------------+---------------------------------------------------------
       socio |        184    3.228261     1.12695          1          5
     married |        184    .6032609    .4905559          0          1
      unempl |        184    .0652174    .2475828          0          1
conservative |        172    1.982558    .8340266          1          3
   supptrade |        184    3.293478    .9058166          1          5

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. *     ****************************************************************  *

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. *                      Randomization Check                              *

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. *     ****************************************************************  *

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. probit control coll_grad lowinc age female union1 socio married unempl conservative

Iteration 0:   log likelihood =  -416.9176  
Iteration 1:   log likelihood = -410.33457  
Iteration 2:   log likelihood =  -410.3282  
Iteration 3:   log likelihood =  -410.3282  

Probit regression                               Number of obs     =        718
                                                LR chi2(9)        =      13.18
                                                Prob > chi2       =     0.1547
Log likelihood =  -410.3282                     Pseudo R2         =     0.0158

------------------------------------------------------------------------------
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   coll_grad |  -.0600775     .10987    -0.55   0.585    -.2754188    .1552637
      lowinc |   .1182991   .1158989     1.02   0.307    -.1088585    .3454567
         age |   .0040574   .0036085     1.12   0.261    -.0030151      .01113
      female |   .1635466   .1059428     1.54   0.123    -.0440974    .3711906
      union1 |   .2237244    .116216     1.93   0.054    -.0040549    .4515036
       socio |   .0224842   .0557617     0.40   0.687    -.0868068    .1317751
     married |   .1713576   .1159151     1.48   0.139    -.0558319     .398547
      unempl |    .072801   .1822207     0.40   0.690    -.2843449     .429947
conservative |  -.0982022   .0781369    -1.26   0.209    -.2513478    .0549434
       _cons |  -1.023595   .2721637    -3.76   0.000    -1.557026    -.490164
------------------------------------------------------------------------------

. 
. probit econ coll_grad lowinc age female union1 socio married unempl conservative

Iteration 0:   log likelihood = -407.55648  
Iteration 1:   log likelihood = -404.49844  
Iteration 2:   log likelihood = -404.49656  
Iteration 3:   log likelihood = -404.49656  

Probit regression                               Number of obs     =        718
                                                LR chi2(9)        =       6.12
                                                Prob > chi2       =     0.7279
Log likelihood = -404.49656                     Pseudo R2         =     0.0075

------------------------------------------------------------------------------
        econ |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   coll_grad |  -.0659084   .1093743    -0.60   0.547     -.280278    .1484613
      lowinc |  -.0458306   .1171156    -0.39   0.696    -.2753729    .1837117
         age |   .0041768   .0036313     1.15   0.250    -.0029404     .011294
      female |   .0484881   .1059674     0.46   0.647    -.1592042    .2561803
      union1 |    .101344   .1169294     0.87   0.386    -.1278334    .3305214
       socio |   .0653386   .0551154     1.19   0.236    -.0426855    .1733628
     married |  -.0039726   .1154988    -0.03   0.973    -.2303461    .2224009
      unempl |   .2072247   .1788791     1.16   0.247    -.1433718    .5578213
conservative |  -.0727662   .0776805    -0.94   0.349    -.2250171    .0794847
       _cons |  -.9936499   .2735294    -3.63   0.000    -1.529758   -.4575422
------------------------------------------------------------------------------

. 
. probit pol coll_grad lowinc age female union1 socio married unempl conservative

Iteration 0:   log likelihood = -394.14719  
Iteration 1:   log likelihood = -387.55488  
Iteration 2:   log likelihood = -387.54537  
Iteration 3:   log likelihood = -387.54537  

Probit regression                               Number of obs     =        718
                                                LR chi2(9)        =      13.20
                                                Prob > chi2       =     0.1536
Log likelihood = -387.54537                     Pseudo R2         =     0.0167

------------------------------------------------------------------------------
         pol |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   coll_grad |   .1599743   .1106354     1.45   0.148     -.056867    .3768157
      lowinc |   -.038352   .1197846    -0.32   0.749    -.2731255    .1964216
         age |  -.0030929   .0036382    -0.85   0.395    -.0102236    .0040378
      female |  -.1573053   .1076718    -1.46   0.144     -.368338    .0537275
      union1 |  -.1175081    .122512    -0.96   0.337    -.3576271     .122611
       socio |  -.0981288   .0563438    -1.74   0.082    -.2085606     .012303
     married |  -.0309669   .1170504    -0.26   0.791    -.2603814    .1984477
      unempl |  -.0266394    .191164    -0.14   0.889    -.4013139    .3480352
conservative |   .1834578    .079176     2.32   0.020     .0282758    .3386398
       _cons |  -.5073911   .2748107    -1.85   0.065     -1.04601    .0312281
------------------------------------------------------------------------------

. 
. probit cult coll_grad lowinc age female union1 socio married unempl conservative

Iteration 0:   log likelihood = -395.30614  
Iteration 1:   log likelihood =   -389.984  
Iteration 2:   log likelihood = -389.97594  
Iteration 3:   log likelihood = -389.97594  

Probit regression                               Number of obs     =        718
                                                LR chi2(9)        =      10.66
                                                Prob > chi2       =     0.2997
Log likelihood = -389.97594                     Pseudo R2         =     0.0135

------------------------------------------------------------------------------
        cult |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   coll_grad |  -.0377197   .1117542    -0.34   0.736     -.256754    .1813145
      lowinc |  -.0608876   .1195704    -0.51   0.611    -.2952412     .173466
         age |  -.0052474   .0035845    -1.46   0.143    -.0122729    .0017782
      female |  -.0699784   .1079749    -0.65   0.517    -.2816054    .1416486
      union1 |  -.2507999   .1247471    -2.01   0.044    -.4952997   -.0063001
       socio |   .0095846   .0560238     0.17   0.864      -.10022    .1193892
     married |  -.1441199   .1161974    -1.24   0.215    -.3718626    .0836228
      unempl |  -.2731954    .196455    -1.39   0.164    -.6582401    .1118493
conservative |  -.0103969   .0787135    -0.13   0.895    -.1646726    .1438787
       _cons |  -.1705603   .2716235    -0.63   0.530    -.7029326    .3618119
------------------------------------------------------------------------------

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. *     ****************************************************************  *

. 
. *                      Table 2 Model1                                   *

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. *     ****************************************************************  *

. 
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. oprobit  supptrade econ pol cult

Iteration 0:   log likelihood = -1000.5206  
Iteration 1:   log likelihood = -998.22044  
Iteration 2:   log likelihood = -998.22035  

Ordered probit regression                       Number of obs     =        773
                                                LR chi2(3)        =       4.60
                                                Prob > chi2       =     0.2035
Log likelihood = -998.22035                     Pseudo R2         =     0.0023

------------------------------------------------------------------------------
   supptrade |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        econ |   .1931766   .1062376     1.82   0.069    -.0150453    .4013986
         pol |   .1995229   .1079473     1.85   0.065    -.0120498    .4110957
        cult |   .1021072   .1084253     0.94   0.346    -.1104025    .3146168
-------------+----------------------------------------------------------------
       /cut1 |  -1.617908   .1019505                     -1.817727   -1.418089
       /cut2 |  -.9334532   .0839405                     -1.097974   -.7689328
       /cut3 |   .3211746   .0793168                      .1657164    .4766327
       /cut4 |   1.557589   .0942268                      1.372907     1.74227
------------------------------------------------------------------------------

. 
. test _b[/cut1] = _b[/cut2]

 ( 1)  [cut1]_cons - [cut2]_cons = 0

           chi2(  1) =   90.94
         Prob > chi2 =    0.0000

. 
. test _b[/cut2] = _b[/cut3]

 ( 1)  [cut2]_cons - [cut3]_cons = 0

           chi2(  1) =  465.74
         Prob > chi2 =    0.0000

. 
. test _b[/cut3] = _b[/cut4]

 ( 1)  [cut3]_cons - [cut4]_cons = 0

           chi2(  1) =  341.17
         Prob > chi2 =    0.0000

. 
. 
. 
. *     ****************************************************************  *

. 
. *                      Table 2 Model2                                   *

. 
. *     ****************************************************************  *

. 
. 
. 
. oprobit  supptrade econ pol cult union1 socio conservative

Iteration 0:   log likelihood = -928.19413  
Iteration 1:   log likelihood = -921.75666  
Iteration 2:   log likelihood = -921.75588  
Iteration 3:   log likelihood = -921.75588  

Ordered probit regression                       Number of obs     =        718
                                                LR chi2(6)        =      12.88
                                                Prob > chi2       =     0.0450
Log likelihood = -921.75588                     Pseudo R2         =     0.0069

------------------------------------------------------------------------------
   supptrade |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        econ |   .2527986   .1101133     2.30   0.022     .0369806    .4686166
         pol |   .2596741   .1127832     2.30   0.021     .0386231    .4807252
        cult |   .1526012   .1122586     1.36   0.174    -.0674216    .3726241
      union1 |   .0855546   .0895029     0.96   0.339     -.089868    .2609771
       socio |  -.0935851   .0428897    -2.18   0.029    -.1776474   -.0095228
conservative |   .0906814   .0602375     1.51   0.132     -.027382    .2087448
-------------+----------------------------------------------------------------
       /cut1 |    -1.7202   .1648617                     -2.043323   -1.397077
       /cut2 |  -1.014945   .1501726                     -1.309278   -.7206126
       /cut3 |   .2359495   .1458364                     -.0498847    .5217837
       /cut4 |   1.493599   .1563842                      1.187091    1.800106
------------------------------------------------------------------------------

. 
. test _b[/cut1] = _b[/cut2]

 ( 1)  [cut1]_cons - [cut2]_cons = 0

           chi2(  1) =   83.94
         Prob > chi2 =    0.0000

. 
. test _b[/cut2] = _b[/cut3]

 ( 1)  [cut2]_cons - [cut3]_cons = 0

           chi2(  1) =  422.49
         Prob > chi2 =    0.0000

. 
. test _b[/cut3] = _b[/cut4]

 ( 1)  [cut3]_cons - [cut4]_cons = 0

           chi2(  1) =  326.10
         Prob > chi2 =    0.0000

. 
. 
. 
. *     ****************************************************************  *

. 
. *                     Table 2 Model3                                    *

. 
. *     ****************************************************************  *

. 
. 
. 
. oprobit  supptrade econ pol cult coll_grad age lowinc female union1 socio married unempl conservative

Iteration 0:   log likelihood = -928.19413  
Iteration 1:   log likelihood = -900.04158  
Iteration 2:   log likelihood = -900.01637  
Iteration 3:   log likelihood = -900.01637  

Ordered probit regression                       Number of obs     =        718
                                                LR chi2(12)       =      56.36
                                                Prob > chi2       =     0.0000
Log likelihood = -900.01637                     Pseudo R2         =     0.0304

------------------------------------------------------------------------------
   supptrade |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        econ |    .250014   .1107611     2.26   0.024     .0329263    .4671017
         pol |   .2094449   .1138842     1.84   0.066    -.0137639    .4326537
        cult |   .1336935   .1133822     1.18   0.238    -.0885316    .3559185
   coll_grad |   .4224193   .0870946     4.85   0.000      .251717    .5931217
         age |    .002819   .0028251     1.00   0.318     -.002718     .008356
      lowinc |  -.0425143   .0918539    -0.46   0.643    -.2225446     .137516
      female |  -.2533578   .0838447    -3.02   0.003    -.4176904   -.0890253
      union1 |   .0220095   .0936058     0.24   0.814    -.1614545    .2054734
       socio |  -.0814841   .0436135    -1.87   0.062    -.1669651    .0039968
     married |  -.0049828   .0905179    -0.06   0.956    -.1823947    .1724291
      unempl |   -.129671   .1448391    -0.90   0.371    -.4135505    .1542085
conservative |   .0754829    .061315     1.23   0.218    -.0446922     .195658
-------------+----------------------------------------------------------------
       /cut1 |  -1.619752   .2406315                     -2.091381   -1.148123
       /cut2 |  -.9132412    .230353                     -1.364725   -.4617575
       /cut3 |     .37642   .2280484                     -.0705466    .8233866
       /cut4 |    1.69508   .2368364                      1.230889    2.159271
------------------------------------------------------------------------------

. 
. test _b[/cut1] = _b[/cut2]

 ( 1)  [cut1]_cons - [cut2]_cons = 0

           chi2(  1) =   83.65
         Prob > chi2 =    0.0000

. 
. test _b[/cut2] = _b[/cut3]

 ( 1)  [cut2]_cons - [cut3]_cons = 0

           chi2(  1) =  423.98
         Prob > chi2 =    0.0000

. 
. test _b[/cut3] = _b[/cut4]

 ( 1)  [cut3]_cons - [cut4]_cons = 0

           chi2(  1) =  325.46
         Prob > chi2 =    0.0000

. 
. 
. 
. 
. 
. *     ****************************************************************  *

. 
. *       Predicted Prob w/ Clarify   Table 3                             *

. 
. *     ****************************************************************  *

. 
. 
. 
. estsimp oprobit supptrade econ pol cult union1 socio conservative

Iteration 0:   log likelihood = -928.19413
Iteration 1:   log likelihood = -921.75666
Iteration 2:   log likelihood = -921.75588

Ordered probit estimates                          Number of obs   =        718
                                                  LR chi2(6)      =      12.88
                                                  Prob > chi2     =     0.0450
Log likelihood = -921.75588                       Pseudo R2       =     0.0069

------------------------------------------------------------------------------
   supptrade |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        econ |   .2527986   .1101132     2.30   0.022     .0369806    .4686166
         pol |   .2596741   .1127832     2.30   0.021     .0386231    .4807252
        cult |   .1526012   .1122586     1.36   0.174    -.0674216    .3726241
      union1 |   .0855546   .0895029     0.96   0.339    -.0898679    .2609771
       socio |  -.0935851   .0428897    -2.18   0.029    -.1776474   -.0095228
conservative |   .0906814   .0602375     1.51   0.132     -.027382    .2087448
-------------+----------------------------------------------------------------
       _cut1 |    -1.7202   .1648617          (Ancillary parameters)
       _cut2 |  -1.014945   .1501725 
       _cut3 |   .2359495   .1458364 
       _cut4 |   1.493599   .1563842 
------------------------------------------------------------------------------

Simulating main parameters.  Please wait....

Note: Clarify is expanding your dataset from 773 observations to 1000
observations in order to accommodate the simulations.  This will append
missing values to the bottom of your original dataset.

% of simulations completed: 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7 b8 b9 b10

. 
. 
. 
. *     ****************************************************************  *

. 
. *      Control Group                                                    *

. 
. *     ****************************************************************  *

. 
. 
. 
. setx econ 0 pol 0 cult 0 union1 median socio median conservative median

. 
. simqi,  genpr(con0 con1 con2 con3 con4)

Simqi generated the following new variable(s): con0 con1 con2 con3 con4

. 
. 
. 
. *     ****************************************************************  *

. 
. *       Wealthy Treatment Group                                         *

. 
. *     ****************************************************************  *

. 
. 
. 
. setx econ 1 pol 0 cult 0 union1 median socio median conservative median

. 
. simqi,  genpr(wea0 wea1 wea2 wea3 wea4)

Simqi generated the following new variable(s): wea0 wea1 wea2 wea3 wea4

. 
. 
. 
. *     ****************************************************************  *

. 
. *       Politics Treatment Group                                        *

. 
. *     ****************************************************************  *

. 
. 
. 
. setx econ 0 pol 1 cult 0 union1 median socio median conservative median

. 
. simqi,  genpr(pol0 pol1 pol2 pol3 pol4)

Simqi generated the following new variable(s): pol0 pol1 pol2 pol3 pol4

. 
. 
. 
. *     ****************************************************************  *

. 
. *       Culture Treatment Group                                         *

. 
. *     ****************************************************************  *

. 
. 
. 
. setx econ 0 pol 0 cult 1 union1 median socio median conservative median

. 
. simqi,  genpr(cul0 cul1 cul2 cul3 cul4)

Simqi generated the following new variable(s): cul0 cul1 cul2 cul3 cul4

. 
. 
. 
. *     ****************************************************************  *

. 
. *      difference between wealthy treatment and Control                 *

. 
. *     ****************************************************************  *

. 
. 
. 
. gen wcdiff4 = wea4-con4

. 
. 
. 
. *     ****************************************************************  *

. 
. *      difference between Politics treatment and Control                *

. 
. *     ****************************************************************  *

. 
. 
. 
. gen pcdiff4 = pol4-con4

. 
. 
. 
. *     ****************************************************************  *

. 
. 
. 
. *      difference between Culture treatment and Control                 *

. 
. *     ****************************************************************  *

. 
. 
. 
. gen ccdiff4 = cul4-con4

. 
. 
. 
. *     ****************************************************************  *

. 
. *     Centiles                                                          *

. 
. *     ****************************************************************  *

. 
. 
. 
. centile  wea4, centile (2.5 50 97.5) 

                                                       -- Binom. Interp. --
    Variable |       Obs  Percentile    Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
        wea4 |     1,000        2.5    .0617239        .0577365    .0633498
             |                   50    .0894054        .0880105    .0909482
             |                 97.5    .1284388        .1247262    .1319053

. 
. centile cul4, centile (2.5 50 97.5)

                                                       -- Binom. Interp. --
    Variable |       Obs  Percentile    Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
        cul4 |     1,000        2.5    .0500655        .0478846    .0522239
             |                   50    .0761254        .0746811    .0776477
             |                 97.5    .1090584        .1064412    .1126712

. 
. centile pol4, centile (2.5 50 97.5)

                                                       -- Binom. Interp. --
    Variable |       Obs  Percentile    Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
        pol4 |     1,000        2.5    .0608533        .0580141    .0636008
             |                   50    .0930695        .0917386    .0945586
             |                 97.5    .1272501        .1239523    .1297383

. 
. centile con4, centile (2.5 50 97.5)

                                                       -- Binom. Interp. --
    Variable |       Obs  Percentile    Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
        con4 |     1,000        2.5    .0373745        .0363268    .0379135
             |                   50    .0553296        .0545931    .0562103
             |                 97.5    .0825275        .0800804    .0876734

. 
. centile  wcdiff4  pcdiff4  ccdiff4, centile (2.5 50 97.5)

                                                       -- Binom. Interp. --
    Variable |       Obs  Percentile    Centile        [95% Conf. Interval]
-------------+-------------------------------------------------------------
     wcdiff4 |     1,000        2.5    .0031685        .0007727    .0051645
             |                   50    .0341597        .0328718    .0351243
             |                 97.5    .0674948        .0626476    .0707335
     pcdiff4 |     1,000        2.5    .0047834         .001148    .0074016
             |                   50    .0361582        .0349063    .0377704
             |                 97.5    .0723086        .0666877    .0741988
     ccdiff4 |     1,000        2.5   -.0090666       -.0106135   -.0048716
             |                   50    .0197775        .0188056    .0212066
             |                 97.5     .051902        .0491495     .054219

. 
. 
. 
. *     ****************************************************************  *

. 
. *           Table 2 Model 4                                             *

. 
. *     ****************************************************************  *

. 
. 
. 
. oprobit  supptrade econ pol cult if coll_grad==0

Iteration 0:   log likelihood = -591.67331  
Iteration 1:   log likelihood = -587.69523  
Iteration 2:   log likelihood = -587.69453  
Iteration 3:   log likelihood = -587.69453  

Ordered probit regression                       Number of obs     =        471
                                                LR chi2(3)        =       7.96
                                                Prob > chi2       =     0.0469
Log likelihood = -587.69453                     Pseudo R2         =     0.0067

------------------------------------------------------------------------------
   supptrade |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        econ |   .2932156   .1345848     2.18   0.029     .0294342     .556997
         pol |   .3265654   .1407555     2.32   0.020     .0506897     .602441
        cult |   .3214657   .1396921     2.30   0.021     .0476742    .5952573
-------------+----------------------------------------------------------------
       /cut1 |  -1.423105   .1230971                     -1.664371   -1.181839
       /cut2 |  -.7529013   .1037892                     -.9563243   -.5494782
       /cut3 |    .656479    .102174                      .4562217    .8567363
       /cut4 |    1.87975    .131033                       1.62293     2.13657
------------------------------------------------------------------------------

. 
. test _b[/cut1] = _b[/cut2]

 ( 1)  [cut1]_cons - [cut2]_cons = 0

           chi2(  1) =   61.48
         Prob > chi2 =    0.0000

. 
. test _b[/cut2] = _b[/cut3]

 ( 1)  [cut2]_cons - [cut3]_cons = 0

           chi2(  1) =  341.50
         Prob > chi2 =    0.0000

. 
. test _b[/cut3] = _b[/cut4]

 ( 1)  [cut3]_cons - [cut4]_cons = 0

           chi2(  1) =  160.11
         Prob > chi2 =    0.0000

. 
. 
. 
. *     ****************************************************************  *

. 
. *            Interactions                                               *

. 
. *     ****************************************************************  *

. 
. 
. 
. gen collxecon = coll_grad*econ
(227 missing values generated)

. 
. gen collxpol = coll_grad*pol
(227 missing values generated)

. 
. gen collxcult = coll_grad*cult
(227 missing values generated)

. 
. 
. 
. *     ****************************************************************  *

. 
. *                      Table 2 Model 4                                  *

. 
. *     ****************************************************************  *

. 
. 
. 
. oprobit  supptrade econ pol cult coll_grad collxecon collxpol collxcult

Iteration 0:   log likelihood = -1000.5206  
Iteration 1:   log likelihood = -979.21859  
Iteration 2:   log likelihood = -979.20768  
Iteration 3:   log likelihood = -979.20768  

Ordered probit regression                       Number of obs     =        773
                                                LR chi2(7)        =      42.63
                                                Prob > chi2       =     0.0000
Log likelihood = -979.20768                     Pseudo R2         =     0.0213

------------------------------------------------------------------------------
   supptrade |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        econ |   .2860637   .1337229     2.14   0.032     .0239716    .5481558
         pol |   .3156067   .1397871     2.26   0.024      .041629    .5895844
        cult |   .3104199   .1387468     2.24   0.025     .0384813    .5823586
   coll_grad |   .7447171   .1580238     4.71   0.000     .4349962    1.054438
   collxecon |  -.2528646   .2215263    -1.14   0.254    -.6870481     .181319
    collxpol |  -.3782009   .2220932    -1.70   0.089    -.8134955    .0570937
   collxcult |  -.5880518   .2246544    -2.62   0.009    -1.028366   -.1477372
-------------+----------------------------------------------------------------
       /cut1 |  -1.384872   .1150522                      -1.61037   -1.159374
       /cut2 |  -.6907309   .0998404                     -.8864146   -.4950473
       /cut3 |   .5968724   .0987789                      .4032694    .7904754
       /cut4 |   1.875343   .1147359                      1.650464    2.100221
------------------------------------------------------------------------------

. 
. test _b[/cut1] = _b[/cut2]

 ( 1)  [cut1]_cons - [cut2]_cons = 0

           chi2(  1) =   90.99
         Prob > chi2 =    0.0000

. 
. test _b[/cut2] = _b[/cut3]

 ( 1)  [cut2]_cons - [cut3]_cons = 0

           chi2(  1) =  466.05
         Prob > chi2 =    0.0000

. 
. test _b[/cut3] = _b[/cut4]

 ( 1)  [cut3]_cons - [cut4]_cons = 0

           chi2(  1) =  341.41
         Prob > chi2 =    0.0000

. 
. 
. 
. *     ****************************************************************  *

. 
. *                     Table 2 Model 4                                  *

. 
. *     ****************************************************************  *

. 
. 
. 
. oprobit  supptrade econ pol cult coll_grad collxecon collxpol collxcult age lowinc female union1 socio married unempl conservative

Iteration 0:   log likelihood = -928.19413  
Iteration 1:   log likelihood = -896.08093  
Iteration 2:   log likelihood = -896.04653  
Iteration 3:   log likelihood = -896.04653  

Ordered probit regression                       Number of obs     =        718
                                                LR chi2(15)       =      64.30
                                                Prob > chi2       =     0.0000
Log likelihood = -896.04653                     Pseudo R2         =     0.0346

------------------------------------------------------------------------------
   supptrade |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        econ |   .3351122   .1413525     2.37   0.018     .0580663    .6121581
         pol |   .3941232   .1496483     2.63   0.008     .1008178    .6874285
        cult |   .3708915   .1455497     2.55   0.011     .0856194    .6561636
   coll_grad |   .7391919   .1648668     4.48   0.000     .4160589    1.062325
   collxecon |  -.2237358   .2291423    -0.98   0.329    -.6728465    .2253748
    collxpol |  -.4554375   .2298681    -1.98   0.048    -.9059707   -.0049044
   collxcult |  -.6070538   .2317801    -2.62   0.009    -1.061335   -.1527731
         age |   .0023546   .0028355     0.83   0.406    -.0032028    .0079121
      lowinc |  -.0495272   .0921469    -0.54   0.591    -.2301319    .1310774
      female |  -.2449382   .0839703    -2.92   0.004    -.4095169   -.0803595
      union1 |   .0191583   .0937083     0.20   0.838    -.1645066    .2028232
       socio |  -.0761776   .0437028    -1.74   0.081    -.1618335    .0094783
     married |   .0045541   .0909935     0.05   0.960    -.1737899    .1828981
      unempl |  -.1369221   .1449864    -0.94   0.345    -.4210903    .1472461
conservative |   .0748682   .0614225     1.22   0.223    -.0455177    .1952541
-------------+----------------------------------------------------------------
       /cut1 |   -1.51585   .2456574                      -1.99733   -1.034371
       /cut2 |  -.8035022   .2357438                     -1.265552   -.3414527
       /cut3 |   .4952367   .2341682                      .0362754    .9541979
       /cut4 |   1.820594   .2432131                      1.343905    2.297283
------------------------------------------------------------------------------

. 
. test _b[/cut1] = _b[/cut2]

 ( 1)  [cut1]_cons - [cut2]_cons = 0

           chi2(  1) =   83.73
         Prob > chi2 =    0.0000

. 
. test _b[/cut2] = _b[/cut3]

 ( 1)  [cut2]_cons - [cut3]_cons = 0

           chi2(  1) =  423.12
         Prob > chi2 =    0.0000

. 
. test _b[/cut3] = _b[/cut4]

 ( 1)  [cut3]_cons - [cut4]_cons = 0

           chi2(  1) =  325.62
         Prob > chi2 =    0.0000

. exit, clear
